Using Dynamic Virtual Microscopy to Train Pathology Residents During the Pandemic: Perspectives on Pathology Education in the Age of COVID-19 Paper by Drs. Robert J. Christian, MD, MS & Mandy VanSandt, DO (Oregon Health & Science University) Abstract: The...
Microscope-Based Automated Quantification of Liver Fibrosis in Mice Using a Deep Learning Algorithm AI Algorithms Developed by AIRA Matrix Within Augmentiqs Abstract: In preclinical studies that involve animal models for hepatic fibrosis, accurate quantification of...
In honor of Dr. Juan Rosai (1940-2020), a paper written in 2007. “Recent years have seen increasing predictions of the demise of conventional microscopy in patient care and investigative medicine. However, these predictions fail to recognize the power of...
Abstract: Quantification of fatty vacuoles in the liver, with differentiation from lumina of liver blood vessels and bile ducts, is an example where the traditional semiquantitative pathology assessment can be enhanced with artificial intelligence (AI) algorithms....
Augmentiqs Augmented Reality of Microscope Cited as Enabling Technology for Artificial Intelligence in Toxicologic Pathology The Society of Toxicologic Pathology Digital Pathology and Image Analysis Special Interest Group, consisting of toxicologic pathologists from...
Augmentiqs is a solution for microscope-based digital pathology. Our technology enables pathology labs to reduce costs and increase clinical excellence.
